Francisco das Chagas Vasconcelos Júnior

Projeções de mudanças na precipitação e temperatura no nordeste brasileiro utilizando a técnica de downscaling dinâmico

This paper presents analysis of projected changes on precipitation and temperature perfomed by dynamical downscaling simulations in the CORDEX Project context. The simulation domain encompasses the Tropical Americas but the focus of this study is restricted to the Northeast Brazil subregions: North (NNEB) and South (SNEB). The regional model run in the simulations was RAMS6.0, forced by HadGEM2-ES global model data. The present period and three future time slices under the RCP8.5 climate scenario were analyzed. Current precipitation and temperature were compared against CRU observed data, to evaluate the performance and the biases from the regional and the global model. In comparison to the HadGEM2-ES model, RAMS6.0 is superior in some aspects as the phase representation of the annual precipitation and temperature cycle, reduction of the dry bias during the dry season over the NNEB and spatial distribution of the two variables, especially temperature. However, RAMS6.0 exacerbates some errors from the global model, like the wet bias in the rainy season. In the future climate, changes in the climatological value and annual mean fields of both variables were analyzed. Some patterns were projected by both models, like decreasing precipitation during austral winter and increasing temperature throughout the century.

Monthly streamflow forecast for National Interconnected System (NIS) using Periodic Auto-regressive Endogenous Models (PAR) and Exogenous (PARX) with climate information

This study aims to find a seasonal streamflow forecast model simultaneous to all stations of SIN using periodic autoregressive models with exogenous variables (PARX) using climate indexes. Comparing the results from PAR and PARX Models, this research analyzes the impact on forecasts by using climate information. The proposed models for streamflow forecast has been carried out using natural streamflow data from Operador Nacional do Sistema (ONS) and statistical techniques (such as multiple linear regression and stepwise method to choose explanatory variables). On 27 climate indexes utilized, 4 of them are suggested in this work. The performance analysis methodology is based on the ELECTRE method further the NASH coefficient, the mean absolute percentage error, the multi-criteria distance and correlation. Forecasts with one month lead, the PAR models present better results for most stations of SIN within seasons DJF, MAM, and JJA, while for SON season there is greater efficiency from PARX model. This kind of model shows better performance during dry season in the basins at Northern Brazil – Amazonas and Araguaia-Tocantins; Central-Eastern Brazil – Eastern Atlantic and the most rivers located in the Paraná basin.

Projeções de Mudanças Climáticas sobre o Nordeste Brasileiro dos Modelos do CMIP5 e do CORDEX

This work addresses the performance and projections of climate simulations from CMIP5 global models and CORDEX regional climate models over Northeast Brazil (NEB). For this study, NEB climate was characterized by the following variables: near surface air temperature (TAS), precipitation (PR), potential evapotranspiration (ETo), and aridity index (IA). In verification methodology of the models we utilized statistical metrics such as mean square error, statistical bias, Pearson correlation and concordance index. In general, the ensemble mean of the simulations (M) produces a significant representation of NEB recent (1985-2005) climate. The projections of M for scenarios of future emissions of greenhouse gases, RCP4.5 and RCP8.5, show generalized increase in the temperature, with 2079-2099 (long-term) temperature anomalies over NEB ranging between 2.1 °C (RCP4.5) and 4 °C (RCP8.5). The ETo rates are more likely to increase during the 21st century, with the RCP8.5 long-term mean 15% higher than reference values for recent climate. Projection of precipitation is inconclusive due to significant spread among the individual simulations, with M indicating a anomaly of −1.6% in RCP8.5 long-term mean. Projected IA is reduced in most simulations of future climate, suggesting a greater chance of increased aridity over NEB during this century.

Evaluation of the AR4 CMIP3 and the AR5 CMIP5 Model and Projections for Precipitation in Northeast Brazil

With the simulations of the models used in the latest reports from the Intergovernmental Panel on Climate Change (IPCC), comparative studies are necessary between observations and the so-called historical run (C20) and future projections of the AR4 (A2) and AR5 (RCP8.5) experiments, in order to assess whether the AR5 models had a better performance in the representation of physical processes. This article compares the sensitivity of IPCC models (AR4 and AR5) in representing the anuall average and seasonal rainfall variation (summer and autumn) in three regions of the Northeast of Brazil between 1979 and 2000, using the CMAP - CPC (Merged Analysis of Precipitation) data as reference. The projections made by these models for the period 2040-2070 were also analyzed.